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Zhang N, Huang Y, Wang G, Xiang Y, Jing Z, Zeng J, Yu F, Pan X, Zhou W, Zeng X. Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer. Breast Cancer Res 2024; 26:64. [PMID: 38610016 PMCID: PMC11010353 DOI: 10.1186/s13058-024-01813-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 03/20/2024] [Indexed: 04/14/2024] Open
Abstract
BACKGROUND This study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients. METHODS A total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre‑therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines. RESULTS Twenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels. CONCLUSION Serum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.
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Affiliation(s)
- Ningning Zhang
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Yuxin Huang
- Department of Breast Cancer Center, School of Medicine, Chongqing University Cancer Hospital, Chongqing University, Chongqing, China
| | - Guanwen Wang
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Yimei Xiang
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Zhouhong Jing
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Junjie Zeng
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Feng Yu
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Xianjun Pan
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Wenqi Zhou
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Xiaohua Zeng
- Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.
- Department of Breast Cancer Center, School of Medicine, Chongqing University Cancer Hospital, Chongqing University, Chongqing, China.
- Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing University Cancer Hospital, Chongqing, China.
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García-Perdomo HA, Dávila-Raigoza AM, Korkes F. Metabolomics for the diagnosis of bladder cancer: A systematic review. Asian J Urol 2024; 11:221-241. [PMID: 38680576 PMCID: PMC11053311 DOI: 10.1016/j.ajur.2022.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 11/29/2022] [Indexed: 05/01/2024] Open
Abstract
Objective Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis. Methods A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy. Results The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism. Conclusion The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.
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Affiliation(s)
- Herney Andrés García-Perdomo
- Division of Urology/Urooncology, Department of Surgery, School of Medicine, Universidad del Valle, Cali, Colombia
- UROGIV Research Group, School of Medicine, Universidad del Valle, Cali, Colombia
| | | | - Fernando Korkes
- Urologic Oncology, Division of Urology, ABC Medical School, Sao Paulo, Brazil
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Bel’skaya LV, Gundyrev IA, Solomatin DV. The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review. Curr Issues Mol Biol 2023; 45:7513-7537. [PMID: 37754258 PMCID: PMC10527988 DOI: 10.3390/cimb45090474] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 09/05/2023] [Accepted: 09/12/2023] [Indexed: 09/28/2023] Open
Abstract
This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.
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Affiliation(s)
- Lyudmila V. Bel’skaya
- Biochemistry Research Laboratory, Omsk State Pedagogical University, 644099 Omsk, Russia;
| | - Ivan A. Gundyrev
- Biochemistry Research Laboratory, Omsk State Pedagogical University, 644099 Omsk, Russia;
| | - Denis V. Solomatin
- Department of Mathematics and Mathematics Teaching Methods, Omsk State Pedagogical University, 644043 Omsk, Russia;
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Zapater-Moros A, Díaz-Beltrán L, Gámez-Pozo A, Trilla-Fuertes L, Lumbreras-Herrera MI, López-Camacho E, González-Olmedo C, Espinosa E, Zamora P, Sánchez-Rovira P, Fresno Vara JÁ. Metabolomics unravels subtype-specific characteristics related to neoadjuvant therapy response in breast cancer patients. Metabolomics 2023; 19:60. [PMID: 37344702 DOI: 10.1007/s11306-023-02024-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 06/09/2023] [Indexed: 06/23/2023]
Abstract
INTRODUCTION Breast cancer is the most diagnosed tumor and the leading cause of cancer death in women worldwide. Metabolomics allows the quantification of the entire set of metabolites in blood samples, making it possible to study differential metabolomics patterns related to neoadjuvant treatment in the breast cancer neoadjuvant setting. OBJECTIVES Characterizing metabolic differences in breast cancer blood samples according to their response to neoadjuvant treatment. METHODS One hundred and three plasma samples of breast cancer patients, before receiving neoadjuvant treatment, were analyzed through UPLC-MS/MS metabolomics. Then, metabolomics data were analyzed using probabilistic graphical models and biostatistics methods. RESULTS Metabolomics data allowed the identification of differences between groups according to response to neoadjuvant treatment. These differences were specific to each breast cancer subtype. Patients with HER2+ tumors showed differences in metabolites related to amino acids and carbohydrates pathways between the two pathological response groups. However, patients with triple-negative tumors showed differences in metabolites related to the long-chain fatty acids pathway. Patients with Luminal B tumors showed differences in metabolites related to acylcarnitine pathways. CONCLUSIONS It is possible to identify differential metabolomics patterns between complete and partial responses to neoadjuvant therapy, being this metabolomic profile specific for each breast cancer subtype.
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Affiliation(s)
- Andrea Zapater-Moros
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
- Biomedica Molecular Medicine SL, C/Faraday 7, 28049, Madrid, Spain
- Biomedical Research Networking Center On Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain
| | - Leticia Díaz-Beltrán
- Systems Biology Unit, Department of Experimental Biology, University of Jaén, Campus Las Lagunillas s/n, 23071, Jaén, Spain
- Medical Oncology Department, Hospital Universitario de Jaén, Av. del Ejército Español, 10, 23007, Jaén, Spain
| | - Angelo Gámez-Pozo
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
- Biomedica Molecular Medicine SL, C/Faraday 7, 28049, Madrid, Spain
| | - Lucía Trilla-Fuertes
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
| | - María Isabel Lumbreras-Herrera
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
| | | | - Carmen González-Olmedo
- Medical Oncology Department, Hospital Universitario de Jaén, Av. del Ejército Español, 10, 23007, Jaén, Spain
| | - Enrique Espinosa
- Medical Oncology Service, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
- Biomedical Research Networking Center On Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain
| | - Pilar Zamora
- Medical Oncology Service, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain
- Biomedical Research Networking Center On Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain
| | - Pedro Sánchez-Rovira
- Medical Oncology Department, Hospital Universitario de Jaén, Av. del Ejército Español, 10, 23007, Jaén, Spain
| | - Juan Ángel Fresno Vara
- Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain.
- Biomedica Molecular Medicine SL, C/Faraday 7, 28049, Madrid, Spain.
- Biomedical Research Networking Center On Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain.
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Suri GS, Kaur G, Carbone GM, Shinde D. Metabolomics in oncology. Cancer Rep (Hoboken) 2023; 6:e1795. [PMID: 36811317 PMCID: PMC10026298 DOI: 10.1002/cnr2.1795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 01/15/2023] [Accepted: 02/10/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND Oncogenic transformation alters intracellular metabolism and contributes to the growth of malignant cells. Metabolomics, or the study of small molecules, can reveal insight about cancer progression that other biomarker studies cannot. Number of metabolites involved in this process have been in spotlight for cancer detection, monitoring, and therapy. RECENT FINDINGS In this review, the "Metabolomics" is defined in terms of current technology having both clinical and translational applications. Researchers have shown metabolomics can be used to discern metabolic indicators non-invasively using different analytical methods like positron emission tomography, magnetic resonance spectroscopic imaging etc. Metabolomic profiling is a powerful and technically feasible way to track changes in tumor metabolism and gauge treatment response across time. Recent studies have shown metabolomics can also predict individual metabolic changes in response to cancer treatment, measure medication efficacy, and monitor drug resistance. Its significance in cancer development and treatment is summarized in this review. CONCLUSION Although in infancy, metabolomics can be used to identify treatment options and/or predict responsiveness to cancer treatments. Technical challenges like database management, cost and methodical knowhow still persist. Overcoming these challenges in near further can help in designing new treatment régimes with increased sensitivity and specificity.
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Affiliation(s)
- Gurparsad Singh Suri
- Department of Biological Sciences, California Baptist University, Riverside, California, USA
| | - Gurleen Kaur
- Department of Biological Sciences, California Baptist University, Riverside, California, USA
| | - Giuseppina M Carbone
- Institute of Oncology Research (IOR), Universita' della Svizzera Italiana (USI), Bellinzona, Switzerland
| | - Dheeraj Shinde
- Institute of Oncology Research (IOR), Universita' della Svizzera Italiana (USI), Bellinzona, Switzerland
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Shekher A, Puneet, Awasthee N, Kumar U, Raj R, Kumar D, Gupta SC. Association of altered metabolic profiles and long non-coding RNAs expression with disease severity in breast cancer patients: analysis by 1H NMR spectroscopy and RT-q-PCR. Metabolomics 2023; 19:8. [PMID: 36710275 DOI: 10.1007/s11306-023-01972-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 01/12/2023] [Indexed: 01/31/2023]
Abstract
INTRODUCTION Globally, one of the major causes of cancer related deaths in women is breast cancer. Although metabolic pattern is altered in cancer patients, robust metabolic biomarkers with a potential to improve the screening and disease monitoring are lacking. A complete metabolome profiling of breast cancer patients may lead to the identification of diagnostic/prognostic markers and potential targets. OBJECTIVES The aim of this study was to analyze the metabolic profile in the serum from 43 breast cancer patients and 13 healthy individuals. MATERIALS & METHODS We used 1H NMR spectroscopy for the identification and quantification of metabolites. q-RT-PCR was used to examine the relative expression of lncRNAs. RESULTS Metabolites such as amino acids, lipids, membrane metabolites, lipoproteins, and energy metabolites were observed in the serum from both patients and healthy individuals. Using unsupervised PCA, supervised PLS-DA, supervised OPLS-DA, and random forest classification, we observed that more than 25 metabolites were altered in the breast cancer patients. Metabolites with AUC value > 0.9 were selected for further analysis that revealed significant elevation of lactate, LPR and glycerol, while the level of glucose, succinate, and isobutyrate was reduced in breast cancer patients in comparison to healthy control. The level of these metabolites (except LPR) was altered in advanced-stage breast cancer patients in comparison to early-stage breast cancer patients. The altered metabolites were also associated with over 25 signaling pathways related to metabolism. Further, lncRNAs such as H19, MEG3 and GAS5 were dysregulated in the breast tumor tissue in comparison to normal adjacent tissue. CONCLUSION The study provides insights into metabolic alteration in breast cancer patients. It also provides an avenue to examine the association of lncRNAs with metabolic patterns in patients.
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Affiliation(s)
- Anusmita Shekher
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India
- Department of General Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India
| | - Puneet
- Department of General Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India
| | - Nikee Awasthee
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India
- Department of Anatomy and Cell Biology, College of Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Umesh Kumar
- Centre of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh, 226 014, India
| | - Ritu Raj
- Centre of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh, 226 014, India
| | - Dinesh Kumar
- Centre of Biomedical Research (CBMR), SGPGIMS, Lucknow, Uttar Pradesh, 226 014, India.
| | - Subash Chandra Gupta
- Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221 005, India.
- Department of Biochemistry, All India Institute of Medical Sciences, Guwahati, Assam, 781101, India.
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Gao Z, Zhou W, Lv X, Wang X. Metabolomics as a Critical Tool for Studying Clinical Surgery. Crit Rev Anal Chem 2023:1-14. [PMID: 36592066 DOI: 10.1080/10408347.2022.2162810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Metabolomics enables the analysis of metabolites within an organism, which offers the closest direct measurement of the physiological activity of the organism, and has advanced efforts to characterize metabolic states, identify biomarkers, and investigate metabolic pathways. A high degree of innovation in analytical techniques has promoted the application of metabolomics, especially in the study of clinical surgery. Metabolomics can be employed as a clinical testing method to maximize therapeutic outcomes, and has been applied in rapid diagnosis of diseases, timely postoperative monitoring, prognostic assessment, and personalized medicine. This review focuses on the use of mass spectrometry and nuclear magnetic resonance-based metabolomics in clinical surgery, including identifying metabolic changes before and after surgery, finding disease-associated biomarkers, and exploring the potential of personalized therapy. Challenges and opportunities of metabolomics in organ transplantation are also discussed, with a particular emphasis on metabolomics in donor organ evaluation and protection, prognostic outcome prediction, as well as postoperative adverse reaction monitoring. In the end, current limitations of metabolomics in clinical surgery and future research directions are presented.
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Affiliation(s)
- Zhenye Gao
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, P. R. China
| | - Wenxiu Zhou
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, P. R. China
| | - Xiaoyuan Lv
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, P. R. China
| | - Xin Wang
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, P. R. China
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Vignoli A, Meoni G, Ghini V, Di Cesare F, Tenori L, Luchinat C, Turano P. NMR-Based Metabolomics to Evaluate Individual Response to Treatments. Handb Exp Pharmacol 2023; 277:209-245. [PMID: 36318327 DOI: 10.1007/164_2022_618] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using 1H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the 1H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.
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Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy. .,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy. .,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy.
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Jin Y, Fan S, Jiang W, Zhang J, Yang L, Xiao J, An H, Ren L. Two effective models based on comprehensive lipidomics and metabolomics can distinguish BC versus HCs, and TNBC versus non-TNBC. Proteomics Clin Appl 2022; 17:e2200042. [PMID: 36443927 DOI: 10.1002/prca.202200042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 10/10/2022] [Accepted: 11/22/2022] [Indexed: 12/03/2022]
Abstract
BACKGROUND Lipidomics and metabolomics are closely related to tumor phenotypes, and serum lipoprotein subclasses and small-molecule metabolites are considered as promising biomarkers for breast cancer (BC) diagnosis. This study aimed to explore potential biomarker models based on lipidomic and metabolomic analysis that could distinguish BC from healthy controls (HCs) and triple-negative BC (TNBC) from non-TNBC. METHODS Blood samples were collected from 114 patients with BC and 75 HCs. A total of 112 types of lipoprotein subclasses and 30 types of small-molecule metabolites in the serum were detected by 1 H-NMR. All lipoprotein subclasses and small-molecule metabolites were subjected to a three-step screening process in the order of significance (p < 0.05), univariate regression (p < 0.1), and lasso regression (nonzero coefficient). Discriminant models of BC versus HCs and TNBC versus non-TNBC were established using binary logistic regression. RESULTS We developed a valid discriminant model based on three-biomarker panel (formic acid, TPA2, and L6TG) that could distinguish patients with BC from HCs. The area under the receiver operating characteristic curve (AUC) was 0.999 (95% confidence interval [CI]: 0.995-1.000) and 0.990 (95% CI: 0.959-1.000) in the training and validation sets, respectively. Based on the panel (D-dimer, CA15-3, CEA, L5CH, glutamine, and ornithine), a discriminant model was established to differentiate between TNBC and non-TNBC, with AUC of 0.892 (95% CI: 0.778-0.967) and 0.905 (95% CI: 0.754-0.987) in the training and validation sets, respectively. CONCLUSION This study revealed lipidomic and metabolomic differences between BC versus HCs and TNBC versus non-TNBC. Two validated discriminatory models established against lipidomic and metabolomic differences can accurately distinguish BC from HCs and TNBC from non-TNBC. IMPACT Two validated discriminatory models can be used for early BC screening and help BC patients avoid time-consuming, expensive, and dangerous BC screening.
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Affiliation(s)
- Yu Jin
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Shuoqing Fan
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Wenna Jiang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jingya Zhang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Lexin Yang
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jiawei Xiao
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Haohua An
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Li Ren
- Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
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How previous treatment changes the metabolomic profile in patients with metastatic breast cancer. Arch Gynecol Obstet 2022; 306:2115-2122. [PMID: 35467121 PMCID: PMC9633507 DOI: 10.1007/s00404-022-06558-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 04/01/2022] [Indexed: 01/29/2023]
Abstract
Purpose Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy. Methods We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ® p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch™ assay. Results We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only. Conclusion We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments.
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11
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Sun L, Cui Z, Huang S, Xue Q, Rehman SU, Luo X, Shi D, Li X. Effect of environmental temperature on semen quality and seminal plasma metabolites of Mediterranean buffalo bulls. Anim Biotechnol 2022; 33:970-980. [PMID: 35352620 DOI: 10.1080/10495398.2022.2056045] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
High-quality semen with high viability is critical to improving the in-vitro fertilization efficiency. This study aimed to understand the effect of ambient temperature and humidity on semen quality and seminal plasma biochemical parameters of Mediterranean buffalo in March and July. The metabolites of seminal plasma in two seasons were detected using the UPLC-MS/MS method. The results showed that temperature and humidity index (THI) in March were 66.86 ± 2.98, and 82.94 ± 3.52 in July. Compared with in March, breath frequency, rectal temperature, and heat shock protein 70 expressions of seminal plasma were significantly increased in July (p < 0.05), motility of sperm was dramatically reduced, and sperm deformity rate was significantly increased (p < 0.05). Fructose, acid phosphatase and α-glucosidase in seminal plasma were significantly increased (p < 0.05) in July, while testosterone level was significantly reduced (p < 0.05). Six different metabolites were found in the two groups, which involved in three metabolic pathways, the tricarboxylic acid cycle, glycerophospholipid, glyoxylic acid and dicarboxylic acid. The above results indicate that the increased ambient temperature has obvious side effects on the semen quality of Mediterranean buffalo, and the compromised quality is associated with the change of metabolites related to male hormone secretion, energy metabolism and fatty acid oxidation.
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Affiliation(s)
- Le Sun
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, P. R. China
| | - Zhichao Cui
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, P. R. China
| | - Shihai Huang
- College of Life Science and Technology, Guangxi University, Nanning, P. R. China
| | - Qingsong Xue
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, P. R. China
| | - Saif Ur Rehman
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, P. R. China
| | - Xi Luo
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, P. R. China
| | - Deshun Shi
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, P. R. China
| | - Xiangping Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, P. R. China
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12
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Magnetic Resonance Imaging (MRI) and MR Spectroscopic Methods in Understanding Breast Cancer Biology and Metabolism. Metabolites 2022; 12:metabo12040295. [PMID: 35448482 PMCID: PMC9030399 DOI: 10.3390/metabo12040295] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 03/22/2022] [Accepted: 03/23/2022] [Indexed: 02/01/2023] Open
Abstract
A common malignancy that affects women is breast cancer. It is the second leading cause of cancer-related death among women. Metabolic reprogramming occurs during cancer growth, invasion, and metastases. Functional magnetic resonance (MR) methods comprising an array of techniques have shown potential for illustrating physiological and molecular processes changes before anatomical manifestations on conventional MR imaging. Among these, in vivo proton (1H) MR spectroscopy (MRS) is widely used for differentiating breast malignancy from benign diseases by measuring elevated choline-containing compounds. Further, the use of hyperpolarized 13C and 31P MRS enhanced the understanding of glucose and phospholipid metabolism. The metabolic profiling of an array of biological specimens (intact tissues, tissue extracts, and various biofluids such as blood, urine, nipple aspirates, and fine needle aspirates) can also be investigated through in vitro high-resolution NMR spectroscopy and high-resolution magic angle spectroscopy (HRMAS). Such studies can provide information on more metabolites than what is seen by in vivo MRS, thus providing a deeper insight into cancer biology and metabolism. The analysis of a large number of NMR spectral data sets through multivariate statistical methods classified the tumor sub-types. It showed enormous potential in the development of new therapeutic approaches. Recently, multiparametric MRI approaches were found to be helpful in elucidating the pathophysiology of cancer by quantifying structural, vasculature, diffusion, perfusion, and metabolic abnormalities in vivo. This review focuses on the applications of NMR, MRS, and MRI methods in understanding breast cancer biology and in the diagnosis and therapeutic monitoring of breast cancer.
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13
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Defining Blood Plasma and Serum Metabolome by GC-MS. Metabolites 2021; 12:metabo12010015. [PMID: 35050137 PMCID: PMC8779220 DOI: 10.3390/metabo12010015] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 12/18/2021] [Accepted: 12/21/2021] [Indexed: 01/04/2023] Open
Abstract
Metabolomics uses advanced analytical chemistry methods to analyze metabolites in biological samples. The most intensively studied samples are blood and its liquid components: plasma and serum. Armed with advanced equipment and progressive software solutions, the scientific community has shown that small molecules’ roles in living systems are not limited to traditional “building blocks” or “just fuel” for cellular energy. As a result, the conclusions based on studying the metabolome are finding practical reflection in molecular medicine and a better understanding of fundamental biochemical processes in living systems. This review is not a detailed protocol of metabolomic analysis. However, it should support the reader with information about the achievements in the whole process of metabolic exploration of human plasma and serum using mass spectrometry combined with gas chromatography.
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Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments. Cancers (Basel) 2021; 13:cancers13184544. [PMID: 34572770 PMCID: PMC8470181 DOI: 10.3390/cancers13184544] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 09/01/2021] [Accepted: 09/08/2021] [Indexed: 12/15/2022] Open
Abstract
Breast cancer (BC) is characterized by high disease heterogeneity and represents the most frequently diagnosed cancer among women worldwide. Complex and subtype-specific gene expression alterations participate in disease development and progression, with BC cells known to rewire their cellular metabolism to survive, proliferate, and invade. Hence, as an emerging cancer hallmark, metabolic reprogramming holds great promise for cancer diagnosis, prognosis, and treatment. Multi-omics approaches (the combined analysis of various types of omics data) offer opportunities to advance our understanding of the molecular changes underlying metabolic rewiring in complex diseases such as BC. Recent studies focusing on the combined analysis of genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics in different BC subtypes have provided novel insights into the specificities of metabolic rewiring and the vulnerabilities that may guide therapeutic development and improve patient outcomes. This review summarizes the findings of multi-omics studies focused on the characterization of the specific metabolic phenotypes of BC and discusses how they may improve clinical BC diagnosis, subtyping, and treatment.
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15
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Mi M, Liu Z, Zheng X, Wen Q, Zhu F, Li J, Mungur ID, Zhang L. Serum metabolomic profiling based on GC/MS helped to discriminate Diffuse Large B-cell Lymphoma patients with different prognosis. Leuk Res 2021; 111:106693. [PMID: 34455197 DOI: 10.1016/j.leukres.2021.106693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 08/15/2021] [Accepted: 08/22/2021] [Indexed: 11/18/2022]
Abstract
BACKGROUND The varied clinical outcomes of patients with Diffuse Large B Cell Lymphoma (DLBCL) are attributed to the different genetic and phenotypic subtypes. The purpose of this study was to determine whether metabolic alterations were related to cell-of-origin subtypes of DLBCL and find some metabolites which are associated with the clinical outcomes. METHODS Pre-treatment serum samples from eighty (80) newly diagnosed DLBCL patients, including twenty-eight (28) patients with Germinal Center B cell-like (GCB) subtypes and fifty-two (52) patients with non-GCB subtypes, were tested by the Gas Chromatography-Mass Spectrometry (GC-MS) technique. Univariate and multivariate analysis methods, principal component analysis (PCA), and partial least square discriminant analysis (PLS-DA) were conducted to examine the potential differential metabolites. Overall survival (OS) was calculated. RESULTS Overall, 65 out of 1472 entities were identified for subsequent analysis. Unfortunately, the initial PLS-DA analysis failed to discriminate GCB from non-GCB samples. Intriguingly, further PLS-DA analysis identified two subgroups of DLBCL (named as group A and group B) and the metabolic subgroups were significantly associated with overall survival. Valine, hexadecenoic acid, and pyroglutamic acid were identified and verified as the most important altered metabolites and could be candidate biomarkers for the prognosis of DLBCL. CONCLUSIONS Our results demonstrated that metabolic alterations in serum could be helpful to predict different clinical outcomes of DLBCL patients. Further studies are warranted to understand whether the altered metabolites might serve as prognostic factors for DLBCL.
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Affiliation(s)
- Mi Mi
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zijian Liu
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xin Zheng
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qiuyue Wen
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fang Zhu
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Juan Li
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ishanee Devi Mungur
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Liling Zhang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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16
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Vignoli A, Risi E, McCartney A, Migliaccio I, Moretti E, Malorni L, Luchinat C, Biganzoli L, Tenori L. Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer. Int J Mol Sci 2021; 22:ijms22094687. [PMID: 33925233 PMCID: PMC8124948 DOI: 10.3390/ijms22094687] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/22/2022] Open
Abstract
Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).
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Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
| | - Emanuela Risi
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Amelia McCartney
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
- School of Clinical Sciences, Monash University, Melbourne 3800, Australia
| | - Ilenia Migliaccio
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Erica Moretti
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Luca Malorni
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
- Correspondence: ; Tel.: +39-055-457-4296
| | - Laura Biganzoli
- Department of Medical Oncology, New Hospital of Prato S. Stefano, 59100 Prato, Italy; (E.R.); (A.M.); (I.M.); (E.M.); (L.M.); (L.B.)
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.)
- Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), 50019 Sesto Fiorentino, Italy
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Febvey-Combes O, Jobard E, Rossary A, Pialoux V, Foucaut AM, Morelle M, Delrieu L, Martin A, Caldefie-Chézet F, Touillaud M, Berthouze SE, Boumaza H, Elena-Herrmann B, Bachmann P, Trédan O, Vasson MP, Fervers B. Effects of an Exercise and Nutritional Intervention on Circulating Biomarkers and Metabolomic Profiling During Adjuvant Treatment for Localized Breast Cancer: Results From the PASAPAS Feasibility Randomized Controlled Trial. Integr Cancer Ther 2021; 20:1534735420977666. [PMID: 33655799 PMCID: PMC7934026 DOI: 10.1177/1534735420977666] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Purpose: Exercise has been shown to improve physical and psychological conditions during cancer therapy, but mechanisms remain poorly understood. The purpose of the present study was to report the results of cancer-related biomarkers and metabolomics outcomes from the PASAPAS feasibility study. Methods: In the PASAPAS randomized controlled trial, 61 women beginning adjuvant chemotherapy for localized breast cancer were randomized in a 6-month program of weekly aerobic exercises associated with nutritional counseling versus usual care with nutritional counseling. In the present analysis of 58 women for whom blood samples were available, first, circulating levels of biomarkers (ie, insulin, insulin-like growth factor 1, estradiol, adiponectin, leptin, interleukin-6, and tumor necrosis factor α) were measured at baseline and 6-month follow-up. Changes in biomarkers were compared between exercisers (n = 40) and controls (n = 18) using mixed-effect models. Second, serum metabolites were studied using an untargeted 1H nuclear magnetic resonance spectroscopy, and orthogonal partial least squares analyses were performed to discriminate exercisers and controls at baseline and at 6 months. Results: Over the 6-month intervention, no statistically significant differences were observed between exercisers and controls regarding changes in biomarkers and metabolomic profiles. Conclusion: The present analysis of the PASAPAS feasibility trial did not reveal any improvement in circulating biomarkers nor identified metabolic signatures in exercisers versus controls during adjuvant breast cancer treatment. Larger studies preferably in women with poor physical activity level to avoid ceiling effect, testing different doses and types of exercise on additional biological pathways, could allow to clarify the mechanisms mediating beneficial effects of physical exercise during cancer treatment. Trial registration: ClinicalTrials.gov Identifier: NCT01331772. Registered 8 April 2011, https://clinicaltrials.gov/ct2/show/NCT01331772?term=pasapas&rank=1
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Affiliation(s)
| | - Elodie Jobard
- Léon Bérard Cancer Center, Lyon, France.,University of Lyon, Villeurbanne, France
| | - Adrien Rossary
- University of Clermont Auvergne, Clermont-Ferrand, France
| | - Vincent Pialoux
- University of Lyon, Villeurbanne, France.,Institut Universitaire de France, Paris, France
| | | | | | - Lidia Delrieu
- Léon Bérard Cancer Center, Lyon, France.,University of Lyon, Villeurbanne, France
| | | | | | - Marina Touillaud
- Léon Bérard Cancer Center, Lyon, France.,Inserm UA8, Lyon, France
| | | | | | | | | | | | - Marie-Paule Vasson
- University of Clermont Auvergne, Clermont-Ferrand, France.,Clermont-Ferrand University Hospital, Jean Perrin Cancer Center, Clermont-Ferrand, France
| | - Béatrice Fervers
- Léon Bérard Cancer Center, Lyon, France.,Inserm UA8, Lyon, France
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18
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Kozar N, Kruusmaa K, Bitenc M, Argamasilla R, Adsuar A, Takač I, Arko D. Identification of Novel Diagnostic Biomarkers in Breast Cancer Using Targeted Metabolomic Profiling. Clin Breast Cancer 2020; 21:e204-e211. [PMID: 33281038 DOI: 10.1016/j.clbc.2020.09.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 09/02/2020] [Accepted: 09/08/2020] [Indexed: 01/01/2023]
Abstract
INTRODUCTION Breast cancer (BC) is the most common cancer in women, with a high disease burden, especially in the advanced disease stages. Our study investigated the metabolomic profile of breast cancer patients' serum with the aim of identifying novel diagnostic biomarkers that could be used, especially for early disease detection. MATERIALS AND METHODS Using targeted metabolomic serum profiling based on high-performance liquid chromatography mass spectrometry, women with BC (n = 39) and a control group (n = 21) were examined for 232 endogenous metabolites. RESULTS The top performing biomarkers included acylcarnitines (ACs) and 9,12-linoleic acid. A combined panel of the top 4 biomarkers achieved 83% sensitivity and 81% specificity, with an area under the curve (AUC) of 0.839 (95% confidence interval, 0.811-0.867). Individual markers also provided significant predictive values: AC 12:0, sensitivity of 72%, specificity of 67%, and AUC of 0.71; AC 14:2, sensitivity of 74%, specificity of 71%, and AUC of 0.73; AC 14:0: sensitivity of 67%, specificity of 81%, and AUC of 0.73; and 9,12-linoleic acid, sensitivity of 69%, specificity of 67%, and AUC of 0.71. The individual markers, however, did not reach the high sensitivity and specificity of the 4-biomarker combination. CONCLUSION Using mass spectrometry-targeted metabolomic profiling, ACs and 9,12-linoleic acid were identified as potential diagnostic biomarkers for breast cancer. Additionally, these identified metabolites could provide additional insight into cancer cell metabolism.
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Affiliation(s)
- Nejc Kozar
- Division of Gynaecology and Perinatology, University Medical Centre Maribor, Maribor, Slovenia; Faculty of Medicine, University of Maribor, Maribor, Slovenia.
| | - Kristi Kruusmaa
- Faculty of Pharmacy, University of Ljubljana, Ljubljana, Slovenia; Universal Diagnostics, S.L. Centre of Research Technology and Innovation, University of Seville, Seville, Spain
| | - Marko Bitenc
- Universal Diagnostics, S.L. Centre of Research Technology and Innovation, University of Seville, Seville, Spain
| | - Rosa Argamasilla
- Universal Diagnostics, S.L. Centre of Research Technology and Innovation, University of Seville, Seville, Spain
| | - Antonio Adsuar
- Universal Diagnostics, S.L. Centre of Research Technology and Innovation, University of Seville, Seville, Spain
| | - Iztok Takač
- Division of Gynaecology and Perinatology, University Medical Centre Maribor, Maribor, Slovenia; Faculty of Medicine, University of Maribor, Maribor, Slovenia
| | - Darja Arko
- Division of Gynaecology and Perinatology, University Medical Centre Maribor, Maribor, Slovenia; Faculty of Medicine, University of Maribor, Maribor, Slovenia
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Ashrafian H, Sounderajah V, Glen R, Ebbels T, Blaise BJ, Kalra D, Kultima K, Spjuth O, Tenori L, Salek RM, Kale N, Haug K, Schober D, Rocca-Serra P, O'Donovan C, Steinbeck C, Cano I, de Atauri P, Cascante M. Metabolomics: The Stethoscope for the Twenty-First Century. Med Princ Pract 2020; 30:301-310. [PMID: 33271569 PMCID: PMC8436726 DOI: 10.1159/000513545] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 11/29/2020] [Indexed: 11/19/2022] Open
Abstract
Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.
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Affiliation(s)
- Hutan Ashrafian
- Institute of Global Health Innovation and Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Viknesh Sounderajah
- Institute of Global Health Innovation and Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Robert Glen
- Institute of Global Health Innovation and Department of Surgery and Cancer, Imperial College London, London, United Kingdom
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Timothy Ebbels
- Institute of Global Health Innovation and Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Benjamin J. Blaise
- Institute of Global Health Innovation and Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Dipak Kalra
- Department of Medical Informatics and Statistics, University of Ghent, Ghent, Belgium
| | - Kim Kultima
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Ola Spjuth
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Leonardo Tenori
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Reza M. Salek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Namrata Kale
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Kenneth Haug
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Daniel Schober
- Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle (Saale), Germany
| | - Philippe Rocca-Serra
- Department of Engineering Science, Oxford e-Research Centre, University of Oxford, Oxford, United Kingdom
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Christoph Steinbeck
- Institute for Inorganic and Analytical Chemistry, Friedrich-Schiller-University, Jena, Germany
| | - Isaac Cano
- Hospital Clinic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Pedro de Atauri
- Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona and CIBERHD (CIBER de Enfermedades hepáticas y digestivas), Barcelona, Spain
| | - Marta Cascante
- Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona and CIBERHD (CIBER de Enfermedades hepáticas y digestivas), Barcelona, Spain
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20
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Tayanloo-Beik A, Sarvari M, Payab M, Gilany K, Alavi-Moghadam S, Gholami M, Goodarzi P, Larijani B, Arjmand B. OMICS insights into cancer histology; Metabolomics and proteomics approach. Clin Biochem 2020; 84:13-20. [PMID: 32589887 DOI: 10.1016/j.clinbiochem.2020.06.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 06/01/2020] [Accepted: 06/09/2020] [Indexed: 02/06/2023]
Abstract
Metabolomics as a post-genomic research area comprising different analytical methods for small molecules analysis. One of the underlying applications of metabolomics technology for better disease diagnosis and prognosis is discovering the metabolic pathway differences between healthy individuals and patients. On the other hand, the other noteworthy applications of metabolomics include its effective role in biomarker screening for cancer detection, monitoring, and prediction. In other words, emerging of the metabolomics field can be hopeful to provide a suitable alternative for the common current cancer diagnostic methods especially histopathological tests. Indeed, cancer as a major global issue places a substantial burden on the health care system. Hence, proper management can be beneficial. In this respect, formalin-fixed paraffin-embedded tissue specimens (in histopathological tests) are considered as a valuable source for metabolomics investigations. Interestingly, formalin-fixed paraffin-embedded tissue specimens can provide informative data for cancer management. In general, using these specimens, determining the cancer stage, individual response to the different therapies, personalized risk prediction are possible and high-quality clinical services are the promise of OMICS technologies for cancer disease. However, considering all of these beneficial characteristics, there are still some limitations in this area that need to be addressed in order to optimize the metabolomics utilizations and advancement.
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Affiliation(s)
- Akram Tayanloo-Beik
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Masoumeh Sarvari
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Moloud Payab
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Kambiz Gilany
- Reproductive Immunology Research Center, Avicenna Research Institute, ACECR, Tehran, Iran; Integrative Oncology Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran.
| | - Sepideh Alavi-Moghadam
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Mahdi Gholami
- Department of Toxicology & Pharmacology, Faculty of Pharmacy; Toxicology and Poisoning Research Center, Tehran University of Medical Sciences, Tehran 1416753955, Iran.
| | - Parisa Goodarzi
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Babak Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran; Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
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21
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Li L, Zheng X, Zhou Q, Villanueva N, Nian W, Liu X, Huan T. Metabolomics-Based Discovery of Molecular Signatures for Triple Negative Breast Cancer in Asian Female Population. Sci Rep 2020; 10:370. [PMID: 31941951 PMCID: PMC6962155 DOI: 10.1038/s41598-019-57068-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 12/16/2019] [Indexed: 11/09/2022] Open
Abstract
Triple negative breast cancer (TNBC) is a devastating cancer disease characterized by its poor prognosis, distinct metastatic patterns, and aggressive biological behavior. Research indicates that the prevalence and presentation of TNBC varies among races, with Asian TNBC patients more commonly presenting with large invasive tumors, high node positivity, and high histologic grade. In this work, we applied ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based metabolomics to discover metabolic signatures in Asian female TNBC patients. Serum samples from 31 TNBC patients and 31 healthy controls (CN) were involved in this study. A total of 2860 metabolic features were detected in the serum samples. Among them, 77 metabolites, whose levels were significantly different between TNBC with CN, were confirmed. Using multivariate statistical analysis, literature mining, metabolic network and pathway analysis, we performed an in-depth study of the metabolic alterations in the Asian TNBC population. In addition, we discovered a panel of metabolic signatures that are highly correlated with the 5-year survival rate of the TNBC patients. This metabolomic study provides a better understanding of the metabolic details of TNBC in the Asian population.
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Affiliation(s)
- Lixian Li
- Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, P.R. China. .,Department of Chemistry, University of British Columbia, Vancouver, British Columbia, V6T 1Z1, Canada.
| | - Xiaodong Zheng
- Department of Breast Cancer, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, P.R. China
| | - Qi Zhou
- Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, P.R. China
| | - Nathaniel Villanueva
- Department of Chemistry, University of British Columbia, Vancouver, British Columbia, V6T 1Z1, Canada
| | - Weiqi Nian
- Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, P.R. China.
| | - Xingming Liu
- Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, P.R. China
| | - Tao Huan
- Department of Chemistry, University of British Columbia, Vancouver, British Columbia, V6T 1Z1, Canada.
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22
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Kumari S, Malla RR. Recent advances in metabolomics of triple negative breast cancer. Breast J 2019; 26:498-501. [PMID: 31489744 DOI: 10.1111/tbj.13524] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Revised: 07/09/2019] [Accepted: 07/09/2019] [Indexed: 01/26/2023]
Abstract
Triple-negative Breast Cancer (TNBC) is considered as the most aggressive subtype of breast cancer. Metabolic profiling has a great significance in cancer research due to profound changes in the metabolism of cancer cells. It has been used to investigate the entire set of metabolites and changes associated with it in disease conditions. These changes in the expression levels of metabolites bring functional changes associated with the pharmacological or nutritional intervention. The present minireview presents a brief note on changes associated with TNBC aggressiveness in terms of metabolomics.
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Affiliation(s)
- Seema Kumari
- Cancer Biology Lab, Department of Biochemistry and Bioinformatics, GIS, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India
| | - Rama Rao Malla
- Cancer Biology Lab, Department of Biochemistry and Bioinformatics, GIS, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India
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23
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Jacob M, Lopata AL, Dasouki M, Abdel Rahman AM. Metabolomics toward personalized medicine. MASS SPECTROMETRY REVIEWS 2019; 38:221-238. [PMID: 29073341 DOI: 10.1002/mas.21548] [Citation(s) in RCA: 195] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 09/14/2017] [Indexed: 05/21/2023]
Abstract
Metabolomics, which is the metabolites profiling in biological matrices, is a key tool for biomarker discovery and personalized medicine and has great potential to elucidate the ultimate product of the genomic processes. Over the last decade, metabolomics studies have identified several relevant biomarkers involved in complex clinical phenotypes using diverse biological systems. Most diseases result in signature metabolic profiles that reflect the sums of external and internal cellular activities. Metabolomics has a major role in clinical practice as it represents >95% of the workload in clinical laboratories worldwide. Many of these metabolites require different analytical platforms, such as Nuclear Magnetic Resonance (NMR), Mass Spectrometry (MS), and Ultra Performance Liquid Chromatography (UPLC), while many clinically relevant metabolites are still not routinely amenable to detection using currently available assays. Combining metabolomics with genomics, transcriptomics, and proteomics studies will result in a significantly improved understanding of the disease mechanisms and the pathophysiology of the target clinical phenotype. This comprehensive approach will represent a major step forward toward providing precision medical care, in which individual is accounted for variability in genes, environment, and personal lifestyle. In this review, we compare and evaluate the metabolomics strategies and studies that focus on the discovery of biomarkers that have "personalized" diagnostic, prognostic, and therapeutic value, validated for monitoring disease progression and responses to various management regimens.
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Affiliation(s)
- Minnie Jacob
- Department of Genetics, King Faisal Specialist Hospital and Research Center (KFSH-RC), Riyadh, Saudi Arabia
- Department of Molecular and Cell Biology, Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD, Australia
| | - Andreas L Lopata
- Department of Molecular and Cell Biology, Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, QLD, Australia
| | - Majed Dasouki
- Department of Genetics, King Faisal Specialist Hospital and Research Center (KFSH-RC), Riyadh, Saudi Arabia
| | - Anas M Abdel Rahman
- Department of Genetics, King Faisal Specialist Hospital and Research Center (KFSH-RC), Riyadh, Saudi Arabia
- College of Medicine, Al Faisal University, Riyadh, Saudi Arabia
- Department of Chemistry, Memorial University of Newfoundland, St. John's, NL, Canada
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24
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Current Status and Future Prospects of Clinically Exploiting Cancer-specific Metabolism-Why Is Tumor Metabolism Not More Extensively Translated into Clinical Targets and Biomarkers? Int J Mol Sci 2019; 20:ijms20061385. [PMID: 30893889 PMCID: PMC6471292 DOI: 10.3390/ijms20061385] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 03/14/2019] [Accepted: 03/15/2019] [Indexed: 02/07/2023] Open
Abstract
Tumor cells exhibit a specialized metabolism supporting their superior ability for rapid proliferation, migration, and apoptotic evasion. It is reasonable to assume that the specific metabolic needs of the tumor cells can offer an array of therapeutic windows as pharmacological disturbance may derail the biochemical mechanisms necessary for maintaining the tumor characteristics, while being less important for normally proliferating cells. In addition, the specialized metabolism may leave a unique metabolic signature which could be used clinically for diagnostic or prognostic purposes. Quantitative global metabolic profiling (metabolomics) has evolved over the last two decades. However, despite the technology’s present ability to measure 1000s of endogenous metabolites in various clinical or biological specimens, there are essentially no examples of metabolomics investigations being translated into actual utility in the cancer clinic. This review investigates the current efforts of using metabolomics as a tool for translation of tumor metabolism into the clinic and further seeks to outline paths for increasing the momentum of using tumor metabolism as a biomarker and drug target opportunity.
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25
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McCartney A, Vignoli A, Biganzoli L, Love R, Tenori L, Luchinat C, Di Leo A. Metabolomics in breast cancer: A decade in review. Cancer Treat Rev 2018; 67:88-96. [PMID: 29775779 DOI: 10.1016/j.ctrv.2018.04.012] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 04/09/2018] [Accepted: 04/10/2018] [Indexed: 12/27/2022]
Abstract
Breast cancer (BC) is a heterogeneous disease which has been characterised and stratified by many platforms such as clinicopathological risk factors, genomic assays, computer generated models, and various "-omic" technologies. Genomic, proteomic and transcriptomic analysis in breast cancer research is well established, and metabolomics, which can be considered a downstream manifestation of the former disciplines, is of growing interest. The past decade has seen significant progress made within the field of clinical metabolomic BC research, with several groups demonstrating results with significant promise in the setting of BC screening and biological characterisation, as well as future potential for prognostic metabolomic biomarkers.
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Affiliation(s)
- Amelia McCartney
- "Sandro Pitigliani" Medical Oncology Department, Hospital of Prato, Istituto Toscano Tumori, Prato, Italy
| | - Alessia Vignoli
- Centre for Magnetic Resonance (CERM), University of Florence, Via Sacconi 6, Sesto Fiorentino 50019, Italy
| | - Laura Biganzoli
- "Sandro Pitigliani" Medical Oncology Department, Hospital of Prato, Istituto Toscano Tumori, Prato, Italy
| | - Richard Love
- Department of Mathematics, Statistics and Computer Science, Marquette University, Milawaukee, WI, USA
| | - Leonardo Tenori
- Centre for Magnetic Resonance (CERM), University of Florence, Via Sacconi 6, Sesto Fiorentino 50019, Italy; Department of Clinical and Experimental Medicine, University of Florence, Largo Brambilla 3, Florence 50100, Italy
| | - Claudio Luchinat
- Centre for Magnetic Resonance (CERM), University of Florence, Via Sacconi 6, Sesto Fiorentino 50019, Italy; Department of Chemistry, University of Florence, Via della Lastruccia 3, Sesto Fiorentino 50019, Italy
| | - Angelo Di Leo
- "Sandro Pitigliani" Medical Oncology Department, Hospital of Prato, Istituto Toscano Tumori, Prato, Italy.
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26
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Giskeødegård GF, Madssen TS, Euceda LR, Tessem MB, Moestue SA, Bathen TF. NMR-based metabolomics of biofluids in cancer. NMR IN BIOMEDICINE 2018; 32:e3927. [PMID: 29672973 DOI: 10.1002/nbm.3927] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 02/13/2018] [Accepted: 03/07/2018] [Indexed: 06/08/2023]
Abstract
This review describes the current status of NMR-based metabolomics of biofluids with respect to cancer risk assessment, detection, disease characterization, prognosis, and treatment monitoring. While the metabolism of cancer cells is altered compared with that of non-proliferating cells, the metabolome of blood and urine reflects the entire organism. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, but translation to clinical practice is currently hindered by lack of validation, difficulties in biological interpretation, and non-standardized analytical procedures.
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Affiliation(s)
- Guro F Giskeødegård
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Torfinn S Madssen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Leslie R Euceda
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - May-Britt Tessem
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
| | - Siver A Moestue
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
- Department of Health Science, Nord University, Bodø, Norway
| | - Tone F Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology-NTNU, Trondheim, Norway
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27
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Cala MP, Aldana J, Medina J, Sánchez J, Guio J, Wist J, Meesters RJW. Multiplatform plasma metabolic and lipid fingerprinting of breast cancer: A pilot control-case study in Colombian Hispanic women. PLoS One 2018; 13:e0190958. [PMID: 29438405 PMCID: PMC5810980 DOI: 10.1371/journal.pone.0190958] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2017] [Accepted: 12/22/2017] [Indexed: 01/22/2023] Open
Abstract
Breast cancer (BC) is a highly heterogeneous disease associated with metabolic reprogramming. The shifts in the metabolome caused by BC still lack data from Latin populations of Hispanic origin. In this pilot study, metabolomic and lipidomic approaches were performed to establish a plasma metabolic fingerprint of Colombian Hispanic women with BC. Data from 1H-NMR, GC-MS and LC-MS were combined and compared. Statistics showed discrimination between breast cancer and healthy subjects on all analytical platforms. The differentiating metabolites were involved in glycerolipid, glycerophospholipid, amino acid and fatty acid metabolism. This study demonstrates the usefulness of multiplatform approaches in metabolic/lipid fingerprinting studies to broaden the outlook of possible shifts in metabolism. Our findings propose relevant plasma metabolites that could contribute to a better understanding of underlying metabolic shifts driven by BC in women of Colombian Hispanic origin. Particularly, the understanding of the up-regulation of long chain fatty acyl carnitines and the down-regulation of cyclic phosphatidic acid (cPA). In addition, the mapped metabolic signatures in breast cancer were similar but not identical to those reported for non-Hispanic women, despite racial differences.
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Affiliation(s)
- Mónica P. Cala
- Department of Chemistry, Grupo de Investigación en Química Analítica y Bioanalítica (GABIO), Universidad de los Andes, Bogotá D.C., Colombia
| | - Julian Aldana
- Department of Chemistry, Grupo de Investigación en Química Analítica y Bioanalítica (GABIO), Universidad de los Andes, Bogotá D.C., Colombia
| | - Jessica Medina
- Department of Chemistry, Universidad del Valle, Cali, Colombia
| | - Julián Sánchez
- Liga contra el Cáncer Seccional Bogotá, Bogotá, Colombia
| | - José Guio
- Liga contra el Cáncer Seccional Bogotá, Bogotá, Colombia
| | - Julien Wist
- Department of Chemistry, Universidad del Valle, Cali, Colombia
| | - Roland J. W. Meesters
- Department of Chemistry, Grupo de Investigación en Química Analítica y Bioanalítica (GABIO), Universidad de los Andes, Bogotá D.C., Colombia
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28
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Jiang L, Lee SC, Ng TC. Pharmacometabonomics Analysis Reveals Serum Formate and Acetate Potentially Associated with Varying Response to Gemcitabine-Carboplatin Chemotherapy in Metastatic Breast Cancer Patients. J Proteome Res 2018; 17:1248-1257. [DOI: 10.1021/acs.jproteome.7b00859] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Affiliation(s)
- Limiao Jiang
- Department
of Epidemiology and Biostatistics, MOE Key Lab of Environment and
Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
- Department
of Diagnostic Radiology, National University of Singapore, 5 Lower
Kent Ridge Road, Singapore 119074, Singapore
| | - Soo Chin Lee
- Department
of Haematology-Oncology, National University Cancer Institute, National University Health System, 5 Lower Kent Ridge Road, Singapore 119074, Singapore
- Cancer
Science Institute of Singapore, National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore
| | - Thian C. Ng
- Department
of Diagnostic Radiology, National University of Singapore, 5 Lower
Kent Ridge Road, Singapore 119074, Singapore
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29
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Jové M, Collado R, Quiles JL, Ramírez-Tortosa MC, Sol J, Ruiz-Sanjuan M, Fernandez M, de la Torre Cabrera C, Ramírez-Tortosa C, Granados-Principal S, Sánchez-Rovira P, Pamplona R. A plasma metabolomic signature discloses human breast cancer. Oncotarget 2017; 8:19522-19533. [PMID: 28076849 PMCID: PMC5386702 DOI: 10.18632/oncotarget.14521] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Accepted: 12/26/2016] [Indexed: 01/04/2023] Open
Abstract
PURPOSE Metabolomics is the comprehensive global study of metabolites in biological samples. In this retrospective pilot study we explored whether serum metabolomic profile can discriminate the presence of human breast cancer irrespective of the cancer subtype. METHODS Plasma samples were analyzed from healthy women (n = 20) and patients with breast cancer after diagnosis (n = 91) using a liquid chromatography-mass spectrometry platform. Multivariate statistics and a Random Forest (RF) classifier were used to create a metabolomics panel for the diagnosis of human breast cancer. RESULTS Metabolomics correctly distinguished between breast cancer patients and healthy control subjects. In the RF supervised class prediction analysis comparing breast cancer and healthy control groups, RF accurately classified 100% both samples of the breast cancer patients and healthy controls. So, the class error for both group in and the out-of-bag error were 0. We also found 1269 metabolites with different concentration in plasma from healthy controls and cancer patients; and basing on exact mass, retention time and isotopic distribution we identified 35 metabolites. These metabolites mostly support cell growth by providing energy and building stones for the synthesis of essential biomolecules, and function as signal transduction molecules. The collective results of RF, significance testing, and false discovery rate analysis identified several metabolites that were strongly associated with breast cancer. CONCLUSIONS In breast cancer a metabolomics signature of cancer exists and can be detected in patient plasma irrespectively of the breast cancer type.
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Affiliation(s)
- Mariona Jové
- Department of Experimental Medicine, University of Lleida-Institute for Research in Biomedicine of Lleida (UdL-IRBLleida), Lleida, Spain
| | - Ricardo Collado
- Department of Oncology, Medical Oncology Unit, Hospital San Pedro de Alcántara, Cáceres, Official Postgraduate Programme in Nutrition and Food Technology, University of Granada, Spain
| | - José Luís Quiles
- Institute of Nutrition and Food Technology "José Mataix", Biomedical Research Center, Department of Physiology, University of Granada, Granada, Spain
| | - Mari-Carmen Ramírez-Tortosa
- Institute of Nutrition and Food Technology "José Mataix", Biomedical Research Center, Department of Biochemistry and Molecular Biology II, University of Granada, Granada, Spain
| | - Joaquim Sol
- Department of Experimental Medicine, University of Lleida-Institute for Research in Biomedicine of Lleida (UdL-IRBLleida), Lleida, Spain
| | | | | | | | - Cesar Ramírez-Tortosa
- Department of Pathological Anatomy, Hospital of Jaén, Jaén, Spain.,GENYO, Centre for Genomics and Oncological Research (Pfizer / University of Granada / Andalusian Regional Government), PTS Granada, Granada, Spain
| | | | | | - Reinald Pamplona
- Department of Experimental Medicine, University of Lleida-Institute for Research in Biomedicine of Lleida (UdL-IRBLleida), Lleida, Spain
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30
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Armitage EG, Ciborowski M. Applications of Metabolomics in Cancer Studies. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 965:209-234. [PMID: 28132182 DOI: 10.1007/978-3-319-47656-8_9] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.
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Affiliation(s)
- Emily Grace Armitage
- Centre for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, Universidad CEU San Pablo, Campus Monteprincipe, Madrid, Spain. .,Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation, College of Medical Veterinary and Life Sciences, Sir Graeme Davies Building, University of Glasgow, Glasgow, UK. .,Glasgow Polyomics, Wolfson Wohl Cancer Research Centre, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
| | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
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31
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Richard V, Conotte R, Mayne D, Colet JM. Does the 1H-NMR plasma metabolome reflect the host-tumor interactions in human breast cancer? Oncotarget 2017; 8:49915-49930. [PMID: 28611296 PMCID: PMC5564817 DOI: 10.18632/oncotarget.18307] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Accepted: 04/01/2017] [Indexed: 12/13/2022] Open
Abstract
Breast cancer (BC) is the most common diagnosed cancer and the leading cause of cancer death in women worldwide. There is an obvious need for a better understanding of BC biology. Alterations in the serum metabolome of BC patients have been identified but their clinical significance remains elusive. We evaluated by 1H-Nuclear Magnetic Resonance (1H-NMR) spectroscopy, filtered plasma metabolome of 50 early (EBC) and 15 metastatic BC (MBC) patients. Using Principal Component Analysis, Partial Least-Squares Discriminant Analysis and Hierarchical Clustering we show that plasma levels of glucose, lactate, pyruvate, alanine, leucine, isoleucine, glutamate, glutamine, valine, lysine, glycine, threonine, tyrosine, phenylalanine, acetate, acetoacetate, β-hydroxy-butyrate, urea, creatine and creatinine are modulated across patients clusters. In particular lactate levels are inversely correlated with the tumor size in the EBC cohort (Pearson correlation r = -0.309; p = 0.044). We suggest that, in BC patients, tumor cells could induce modulation of the whole patient's metabolism even at early stages. If confirmed in a lager study these observations could be of clinical importance.
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Affiliation(s)
- Vincent Richard
- Department of Medical Oncology, CHU Ambroise Paré, B-7000 Mons, Belgium
- Laboratory of Human Biology and Toxicology, Faculty of Medicine and Pharmacy, University of Mons, B-7000 Mons, Belgium
- UMHAP, Bioprofiling Unit, B-7000 Mons, Belgium
| | - Raphaël Conotte
- Laboratory of Human Biology and Toxicology, Faculty of Medicine and Pharmacy, University of Mons, B-7000 Mons, Belgium
- UMHAP, Bioprofiling Unit, B-7000 Mons, Belgium
| | - David Mayne
- Unité de Recherche Clinique, CHU Ambroise Paré, B-7000 Mons, Belgium
| | - Jean-Marie Colet
- Laboratory of Human Biology and Toxicology, Faculty of Medicine and Pharmacy, University of Mons, B-7000 Mons, Belgium
- UMHAP, Bioprofiling Unit, B-7000 Mons, Belgium
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32
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Nickler M, Ottiger M, Steuer C, Kutz A, Christ-Crain M, Zimmerli W, Thomann R, Hoess C, Henzen C, Bernasconi L, Huber A, Mueller B, Schuetz P. Time-dependent association of glucocorticoids with adverse outcome in community-acquired pneumonia: a 6-year prospective cohort study. CRITICAL CARE : THE OFFICIAL JOURNAL OF THE CRITICAL CARE FORUM 2017; 21:72. [PMID: 28335807 PMCID: PMC5364618 DOI: 10.1186/s13054-017-1656-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 02/28/2017] [Indexed: 01/21/2023]
Abstract
Background The hypothalamic-pituitary-adrenal stress axis plays a crucial role in community-acquired pneumonia (CAP), with high cortisol being associated with disease severity and corticosteroid treatment resulting in earlier time to recovery. Our aim in the present study was to compare different glucocorticoid hormones, including cortisol, 11-deoxycortisol, cortisone, and corticosterone, regarding their association with short- and long-term adverse outcomes in a well-defined CAP cohort. Methods We prospectively followed 285 patients with CAP from a previous Swiss multicenter trial for a median of 6.1 years and measured different admission glucocorticoid serum levels by liquid chromatography coupled with tandem mass spectrometry. We used adjusted Cox regression models to investigate associations between admission hormone levels and all-cause mortality at different time points. Results Mortality was 5.3% after 30 days and increased to 47.3% after 6 years. High admission cortisol was associated with adverse outcome after 30 days (adjusted OR 3.85, 95% CI 1.10–13.49, p = 0.035). In the long term (i.e.,), however, high admission cortisol was associated with better survival (adjusted HR after 3 years 0.53, 95% CI 0.32–0.89, p = 0.017; adjusted HR after 6 years 0.57, 95% CI 0.36–0.90, p = 0.015). Compared with 11-deoxycortisol, cortisone, and corticosterone, cortisol showed the highest association with mortality. Conclusions Among different glucocorticoid hormones, cortisol showed the highest association with mortality in CAP. Whereas a more pronounced glucocorticoid stress response on hospital admission was associated with higher short-term adverse outcome, long-term outcome was favorable in these patients. These data should support the correct interpretation of glucocorticoid blood data. Electronic supplementary material The online version of this article (doi:10.1186/s13054-017-1656-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Manuela Nickler
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Manuel Ottiger
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Christian Steuer
- Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Alexander Kutz
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Mirjam Christ-Crain
- Division of Endocrinology, Diabetes and Clinical Nutrition, Department of Internal Medicine, University Hospital Basel, Basel, Switzerland.,Medical Faculty, University of Basel, Basel, Switzerland
| | - Werner Zimmerli
- Basel University Medical Clinic Liestal, Liestal, Switzerland
| | - Robert Thomann
- Department of Internal Medicine, Bürgerspital Solothurn, Solothurn, Switzerland
| | - Claus Hoess
- Department of Internal Medicine, Kantonsspital Münsterlingen, Münsterlingen, Switzerland
| | - Christoph Henzen
- Department of Internal Medicine, Kantonsspital Lucerne, Lucerne, Switzerland
| | - Luca Bernasconi
- Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Andreas Huber
- Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Beat Mueller
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.,Medical Faculty, University of Basel, Basel, Switzerland
| | - Philipp Schuetz
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. .,Medical Faculty, University of Basel, Basel, Switzerland.
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Yang Y, Zhang J, Liu Y, Li B, Li J, Zheng L, Wang L. Metabonomic analysis of metastatic lung tissue in breast cancer mice by an integrated NMR-based metabonomics approach. RSC Adv 2017. [DOI: 10.1039/c7ra02069d] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
This study identified the common potential biomarkers for early lung metastasis of breast cancer in two models.
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Affiliation(s)
- Yongxia Yang
- School of Basic Course
- Guangdong Pharmaceutical University
- Guangzhou
- PR China
- Vascular Biology Research Institute
| | - Jingli Zhang
- School of Basic Course
- Guangdong Pharmaceutical University
- Guangzhou
- PR China
- Vascular Biology Research Institute
| | - Ying Liu
- Vascular Biology Research Institute
- Guangdong Pharmaceutical University
- Guangzhou
- PR China
| | - Binglin Li
- School of Basic Course
- Guangdong Pharmaceutical University
- Guangzhou
- PR China
- Vascular Biology Research Institute
| | - Jiangchao Li
- Vascular Biology Research Institute
- Guangdong Pharmaceutical University
- Guangzhou
- PR China
| | - Lingyun Zheng
- School of Basic Course
- Guangdong Pharmaceutical University
- Guangzhou
- PR China
| | - Lijing Wang
- Vascular Biology Research Institute
- Guangdong Pharmaceutical University
- Guangzhou
- PR China
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Jobard E, Trédan O, Postoly D, André F, Martin AL, Elena-Herrmann B, Boyault S. A Systematic Evaluation of Blood Serum and Plasma Pre-Analytics for Metabolomics Cohort Studies. Int J Mol Sci 2016; 17:ijms17122035. [PMID: 27929400 PMCID: PMC5187835 DOI: 10.3390/ijms17122035] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Revised: 11/14/2016] [Accepted: 11/29/2016] [Indexed: 12/11/2022] Open
Abstract
The recent thriving development of biobanks and associated high-throughput phenotyping studies requires the elaboration of large-scale approaches for monitoring biological sample quality and compliance with standard protocols. We present a metabolomic investigation of human blood samples that delineates pitfalls and guidelines for the collection, storage and handling procedures for serum and plasma. A series of eight pre-processing technical parameters is systematically investigated along variable ranges commonly encountered across clinical studies. While metabolic fingerprints, as assessed by nuclear magnetic resonance, are not significantly affected by altered centrifugation parameters or delays between sample pre-processing (blood centrifugation) and storage, our metabolomic investigation highlights that both the delay and storage temperature between blood draw and centrifugation are the primary parameters impacting serum and plasma metabolic profiles. Storing the blood drawn at 4 °C is shown to be a reliable routine to confine variability associated with idle time prior to sample pre-processing. Based on their fine sensitivity to pre-analytical parameters and protocol variations, metabolic fingerprints could be exploited as valuable ways to determine compliance with standard procedures and quality assessment of blood samples within large multi-omic clinical and translational cohort studies.
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Affiliation(s)
- Elodie Jobard
- Univ Lyon, CNRS, Université Claude Bernard Lyon 1, ENS de Lyon, Institut des Sciences Analytiques UMR 5280, 5 rue de la Doua, F-69100 Villeurbanne, France.
- Centre Léon Bérard, Département de Recherche Translationnelle et de l'Innovation, 28 rue Laënnec, 69373 Lyon, CEDEX 08, France.
| | - Olivier Trédan
- Centre Léon Bérard, Département d'oncologie Médicale, 28 rue Laënnec, 69373 Lyon, CEDEX 08, France.
| | - Déborah Postoly
- Centre Léon Bérard, Département de Recherche Translationnelle et de l'Innovation, Génomique des Cancers, 28 rue Laënnec, 69373 Lyon, CEDEX 08, France.
| | - Fabrice André
- Department of Medical Oncology, Gustave Roussy, Université Paris-Saclay, 94805 Villejuif, France.
| | | | - Bénédicte Elena-Herrmann
- Univ Lyon, CNRS, Université Claude Bernard Lyon 1, ENS de Lyon, Institut des Sciences Analytiques UMR 5280, 5 rue de la Doua, F-69100 Villeurbanne, France.
| | - Sandrine Boyault
- Centre Léon Bérard, Département de Recherche Translationnelle et de l'Innovation, Génomique des Cancers, 28 rue Laënnec, 69373 Lyon, CEDEX 08, France.
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Farrokhi Yekta R, Rezaie Tavirani M, Arefi Oskouie A, Mohajeri-Tehrani MR, Soroush AR. The metabolomics and lipidomics window into thyroid cancer research. Biomarkers 2016; 22:595-603. [DOI: 10.1080/1354750x.2016.1256429] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- R. Farrokhi Yekta
- Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - M. Rezaie Tavirani
- Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - A. Arefi Oskouie
- Department of Basic Sciences, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - M. R. Mohajeri-Tehrani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - A. R. Soroush
- Department of Surgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
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Neuronal metabolomics by ion mobility mass spectrometry in cocaine self-administering rats after early and late withdrawal. Anal Bioanal Chem 2016; 408:4233-45. [DOI: 10.1007/s00216-016-9508-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Revised: 02/24/2016] [Accepted: 03/21/2016] [Indexed: 10/21/2022]
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Stenson M, Pedersen A, Hasselblom S, Nilsson-Ehle H, Karlsson BG, Pinto R, Andersson PO. Serum nuclear magnetic resonance-based metabolomics and outcome in diffuse large B-cell lymphoma patients - a pilot study. Leuk Lymphoma 2016; 57:1814-22. [PMID: 26887805 DOI: 10.3109/10428194.2016.1140164] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
The prognosis for diffuse large B-cell lymphoma (DLBCL) patients with early relapse or refractory disease is dismal. To determine if clinical outcome correlated to diverse serum metabolomic profiles, we used (1)H nuclear magnetic resonance (NMR) spectroscopy and compared two groups of DLBCL patients treated with immunochemotherapy: i) refractory/early relapse (REF/REL; n=27) and ii) long-term progression-free (CURED; n = 60). A supervised multivariate analysis showed a separation between the groups. Among discriminating metabolites higher in the REF/REL group were the amino acids lysine and arginine, the degradation product cadaverine and a compound in oxidative stress (2-hydroxybutyrate). In contrast, the amino acids aspartate, valine and ornithine, and a metabolite in the glutathione cycle, pyroglutamate, were higher in CURED patients. Together, our data indicate that NMR-based serum metabolomics can identify a signature for DLBCL patients with high-risk of failing immunochemotherapy, prompting for larger validating studies which could lead to more individualized treatment of this disease.
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Affiliation(s)
- Martin Stenson
- a Section of Hematology, Department of Medicine , Kungälvs Hospital, Sahlgrenska Academy, University of Gothenburg , Gothenburg , Sweden
| | - Anders Pedersen
- b Swedish NMR Centre, University of Gothenburg , Gothenburg , Sweden
| | - Sverker Hasselblom
- c Department of Research , Development and Education, Region Halland , Gothenburg , Sweden
| | - Herman Nilsson-Ehle
- d Section of Hematology and Coagulation, Sahlgrenska University Hospital, Sahlgrenska Academy at the University of Gothenburg , Gothenburg , Sweden
| | | | - Rui Pinto
- e Computational Life Science Cluster, Department of Clinical Chemistry , Umeå University, Umeå and Bioinformatics for Life Sciences (BILS) , Gothenburg , Sweden
| | - Per-Ola Andersson
- f Unit of Hematology, Department of Medicine , Södra Älvsborg Hospital Borås, Sahlgrenska Academy at the University of Gothenburg , Gothenburg , Sweden
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Hart CD, Tenori L, Luchinat C, Di Leo A. Metabolomics in Breast Cancer: Current Status and Perspectives. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2016; 882:217-34. [DOI: 10.1007/978-3-319-22909-6_9] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Abstract
Breast cancer is a global health issue, and as the tumor burden increases, we need to come up with newer, better technologies which are convenient, cheap, rapid, sensitive with a high specificity. Technological advancements in the field of cancer biomarker has led to the development of techniques such as mass spectrometric analysis and microarray analysis in which genes, proteins and hundreds and thousands of metabolites can be identified with the emergence of genomics, proteomics and metabolomics. This research is focused on finding biomarkers for diagnosis, prognosis, staging, treatment response and targets for chemotherapy, generating a panel of markers which provide better clinical information compared to a single marker in the panel. This review briefly summarizes application of genomics and proteomics followed by key concepts and applications of metabolomics in breast cancer, with the conclusion that an integration of the three “OMIC” technologies may hold the key to future biomarker discovery.
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Affiliation(s)
- Naila Irum Hadi
- Dr. Naila Irum Hadi, MBBS, MPhil, PhD fellow. Professor of Pathology, Ziauddin University, Karachi, Pakistan
| | - Qamar Jamal
- Dr. Qamar Jamal, MBBS, MPhil, PhD. Professor of Pathology, Ziauddin University, Karachi, Pakistan
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Jobard E, Blanc E, Négrier S, Escudier B, Gravis G, Chevreau C, Elena-Herrmann B, Trédan O. A serum metabolomic fingerprint of bevacizumab and temsirolimus combination as first-line treatment of metastatic renal cell carcinoma. Br J Cancer 2015; 113:1148-57. [PMID: 26372698 PMCID: PMC4647878 DOI: 10.1038/bjc.2015.322] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 07/20/2015] [Accepted: 08/12/2015] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Renal cell carcinoma is one of the most chemoresistant cancers, and its metastatic form requires administration of targeted therapies based on angiogenesis or mTOR inhibitors. Understanding how these treatments impact the human metabolism is essential to predict the host response and adjust personalised therapies. We present a metabolomic investigation of serum samples from patients with metastatic RCC (mRCC) to identify metabolic signatures associated with targeted therapies. METHODS Pre-treatment and serial on-treatment sera were available for 121 patients participating in the French clinical trial TORAVA, in which 171 randomised patients with mRCC received a bevacizumab and temsirolimus combination (experimental arm A) or a standard treatment: either sunitinib (B) or interferon-α+bevacizumab (C). Metabolic profiles were obtained using nuclear magnetic resonance spectroscopy and compared on-treatment or between treatments. RESULTS Multivariate statistical modelling discriminates serum profiles before and after several weeks of treatment for arms A and C. The combination A causes faster changes in patient metabolism than treatment C, detectable after only 2 weeks of treatment. Metabolites related to the discrimination include lipids and carbohydrates, consistently with the known RCC metabolism and side effects of the drugs involved. Comparison of the metabolic profiles for the three arms shows that temsirolimus, an mTOR inhibitor, is responsible for the faster host metabolism modification observed in the experimental arm. CONCLUSIONS In mRCC, metabolomics shows a faster host metabolism modification induced by a mTOR inhibitor as compared with standard treatments. These results should be confirmed in larger cohorts and other cancer types.
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Affiliation(s)
- Elodie Jobard
- Centre de RMN à Très Hauts Champs, Institut des Sciences Analytiques (CNRS/ENS Lyon/UCB Lyon 1), Université de Lyon, 69100 Villeurbanne, France
- Université de Lyon, Centre Léon Bérard, 69008 Lyon, France
| | - Ellen Blanc
- Université de Lyon, Centre Léon Bérard, 69008 Lyon, France
| | - Sylvie Négrier
- Université de Lyon, Centre Léon Bérard, 69008 Lyon, France
| | | | | | | | - Bénédicte Elena-Herrmann
- Centre de RMN à Très Hauts Champs, Institut des Sciences Analytiques (CNRS/ENS Lyon/UCB Lyon 1), Université de Lyon, 69100 Villeurbanne, France
| | - Olivier Trédan
- Université de Lyon, Centre Léon Bérard, 69008 Lyon, France
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Nickler M, Ottiger M, Steuer C, Huber A, Anderson JB, Müller B, Schuetz P. Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections. Respir Res 2015; 16:125. [PMID: 26471192 PMCID: PMC4608151 DOI: 10.1186/s12931-015-0283-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2015] [Accepted: 09/29/2015] [Indexed: 01/07/2023] Open
Abstract
Metabolic profiling through targeted quantification of a predefined subset of metabolites, performed by mass spectrometric analytical techniques, allows detailed investigation of biological pathways and thus may provide information about the interaction of different organic systems, ultimately improving understanding of disease risk and prognosis in a variety of diseases. Early risk assessment, in turn, may improve patient management in regard to cite-of-care decisions and treatment modalities. Within this review, we focus on the potential of metabolic profiling to improve our pathophysiological understanding of disease and management of patients. We focus thereby on lower respiratory tract infections (LRTI) including community-acquired pneumonia (CAP) and chronic obstructive pulmonary disease (COPD), an important disease responsible for high mortality, morbidity and costs worldwide. Observational data from numerous clinical and experimental studies have provided convincing data linking metabolic blood biomarkers such as lactate, glucose or cortisol to patient outcomes. Also, identified through metabolomic studies, novel innovative metabolic markers such as steroid hormones, biogenic amines, members of the oxidative status, sphingo- and glycerophospholipids, and trimethylamine-N-oxide (TMAO) have shown promising results. Since many uncertainties remain in predicting mortality in these patients, further prospective and retrospective observational studies are needed to uncover metabolic pathways responsible for mortality associated with LRTI. Improved understanding of outcome-specific metabolite signatures in LRTIs may optimize patient management strategies, provide potential new targets for future individual therapy, and thereby improve patients' chances for survival.
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Affiliation(s)
- Manuela Nickler
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.
| | - Manuel Ottiger
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.
| | - Christian Steuer
- Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland.
| | - Andreas Huber
- Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland.
| | | | - Beat Müller
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.
| | - Philipp Schuetz
- Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.
- University Department of Medicine, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland.
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Metabolomics for Biomarker Discovery: Moving to the Clinic. BIOMED RESEARCH INTERNATIONAL 2015; 2015:354671. [PMID: 26090402 PMCID: PMC4452245 DOI: 10.1155/2015/354671] [Citation(s) in RCA: 111] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/03/2014] [Accepted: 12/28/2014] [Indexed: 12/21/2022]
Abstract
To improve the clinical course of diseases, more accurate diagnostic and assessment methods are required as early as possible. In order to achieve this, metabolomics offers new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has become an important tool in clinical research and the diagnosis of human disease and has been applied to discovery and identification of the perturbed pathways. It provides a powerful approach to discover biomarkers in biological systems and offers a holistic approach with the promise to clinically enhance diagnostics. When carried out properly, it could provide insight into the understanding of the underlying mechanisms of diseases, help to identify patients at risk of disease, and predict the response to specific treatments. Currently, metabolomics has become an important tool in clinical research and the diagnosis of human disease and becomes a hot topic. This review will highlight the importance and benefit of metabolomics for identifying biomarkers that accurately screen potential biomarkers of diseases.
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Carotenuto D, Luchinat C, Marcon G, Rosato A, Turano P. The Da Vinci European BioBank: A Metabolomics-Driven Infrastructure. J Pers Med 2015; 5:107-19. [PMID: 25913579 PMCID: PMC4493490 DOI: 10.3390/jpm5020107] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2015] [Revised: 04/02/2015] [Accepted: 04/16/2015] [Indexed: 11/16/2022] Open
Abstract
We present here the organization of the recently-constituted da Vinci European BioBank (daVEB, https://www.davincieuropeanbiobank.org/it). The biobank was created as an infrastructure to support the activities of the Fiorgen Foundation (http://www.fiorgen.net/), a nonprofit organization that promotes research in the field of pharmacogenomics and personalized medicine. The way operating procedures concerning samples and data have been developed at daVEB largely stems from the strong metabolomics connotation of Fiorgen and from the involvement of the scientific collaborators of the foundation in international/European projects aimed to tackle the standardization of pre-analytical procedures and the promotion of data standards in metabolomics.
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Affiliation(s)
- Dario Carotenuto
- Da Vinci European BioBank, FiorGen Foundation, via Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy.
- Department of Chemistry, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy.
| | - Giordana Marcon
- Da Vinci European BioBank, FiorGen Foundation, via Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
| | - Antonio Rosato
- Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy.
- Department of Chemistry, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy.
| | - Paola Turano
- Da Vinci European BioBank, FiorGen Foundation, via Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
- Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy.
- Department of Chemistry, University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy.
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Zhang A, Sun H, Yan G, Wang P, Wang X. Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research. Biomed Chromatogr 2015; 30:7-12. [DOI: 10.1002/bmc.3453] [Citation(s) in RCA: 131] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Revised: 12/27/2014] [Accepted: 01/20/2015] [Indexed: 12/27/2022]
Affiliation(s)
- Aihua Zhang
- National TCM Key Laboratory of Serum Pharmacochemistry, Laboratory of Metabolomics and Chinmedomics, Department of Pharmaceutical Analysis; Heilongjiang University of Chinese Medicine; Heping Road 24 Harbin 150040 China
| | - Hui Sun
- National TCM Key Laboratory of Serum Pharmacochemistry, Laboratory of Metabolomics and Chinmedomics, Department of Pharmaceutical Analysis; Heilongjiang University of Chinese Medicine; Heping Road 24 Harbin 150040 China
| | - Guangli Yan
- National TCM Key Laboratory of Serum Pharmacochemistry, Laboratory of Metabolomics and Chinmedomics, Department of Pharmaceutical Analysis; Heilongjiang University of Chinese Medicine; Heping Road 24 Harbin 150040 China
| | - Ping Wang
- National TCM Key Laboratory of Serum Pharmacochemistry, Laboratory of Metabolomics and Chinmedomics, Department of Pharmaceutical Analysis; Heilongjiang University of Chinese Medicine; Heping Road 24 Harbin 150040 China
| | - Xijun Wang
- National TCM Key Laboratory of Serum Pharmacochemistry, Laboratory of Metabolomics and Chinmedomics, Department of Pharmaceutical Analysis; Heilongjiang University of Chinese Medicine; Heping Road 24 Harbin 150040 China
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Santucci C, Brizzolara S, Tenori L. Comparison of frozen and fresh apple pulp for NMR-based metabolomic analysis. FOOD ANAL METHOD 2015. [DOI: 10.1007/s12161-015-0107-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Roberts JN, Karvonen C, Graham K, Weinfeld M, Joy AA, Koebel M, Morris D, Robson PJ, Johnston RN, Brockton NT. Biobanking in the Twenty-First Century: Driving Population Metrics into Biobanking Quality. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2015; 864:95-114. [DOI: 10.1007/978-3-319-20579-3_8] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Chan ECY, Pasikanti KK, Hong Y, Ho PC, Mahendran R, Raman Nee Mani L, Chiong E, Esuvaranathan K. Metabonomic profiling of bladder cancer. J Proteome Res 2014; 14:587-602. [PMID: 25388527 DOI: 10.1021/pr500966h] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Early diagnosis and life-long surveillance are clinically important to improve the long-term survival of bladder cancer patients. Currently, a noninvasive biomarker that is as sensitive and specific as cystoscopy in detecting bladder tumors is lacking. Metabonomics is a complementary approach for identifying perturbed metabolic pathways in bladder cancer. Significant progress has been made using modern metabonomic techniques to characterize and distinguish bladder cancer patients from control subjects, identify marker metabolites, and shed insights on the disease biology and potential therapeutic targets. With its rapid development, metabonomics has the potential to impact the clinical management of bladder cancer patients in the future by revolutionizing the diagnosis and life-long surveillance strategies and stratifying patients for diagnostic, surgical, and therapeutic clinical trials. An introduction to metabonomics, typical metabonomic workflow, and critical evaluation of metabonomic investigations in identifying biomarkers for the diagnosis of bladder cancer are presented.
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Affiliation(s)
- Eric Chun Yong Chan
- Department of Pharmacy, Faculty of Science, National University of Singapore , 18 Science Drive 4, Singapore 117543, Singapore
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Tamkovich SN, Voytsitskiy VE, Laktionov PP. Modern methods in breast cancer diagnostics. BIOCHEMISTRY (MOSCOW) SUPPLEMENT SERIES B: BIOMEDICAL CHEMISTRY 2014. [DOI: 10.1134/s1990750814040106] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Zhang Y, Song L, Liu N, He C, Li Z. Decreased serum levels of free fatty acids are associated with breast cancer. Clin Chim Acta 2014; 437:31-7. [PMID: 25016244 DOI: 10.1016/j.cca.2014.07.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2014] [Revised: 06/19/2014] [Accepted: 07/01/2014] [Indexed: 12/22/2022]
Abstract
BACKGROUND Changes in the levels of lipids are associated with breast cancer (BC). METHODS Disease-specific serum free fatty acids (FFAs) were quantified using chip-based direct-infusion nanoelectrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry (CBDInanoESI-FTICR MS) in the negative ion mode. Multiple point internal standard calibration curves between the concentration ratios of fatty acids (i.e., C16:1, C18:3, C18:2, C18:1, C20:4, and C22:6) to internal standards (C17:1 for C16:1, C18:3, C18:2, and C18:1, C21:0 for C20:4 and C22:6) and their corresponding intensity ratios were established with a correlation coefficient of greater than 0.986. RESULTS Data from 342 serum samples including 202 healthy controls and 140 BC patients indicate that serum concentrations of FFAs in patients with BC were significantly decreased compared with those in healthy controls. A panel of C16:1, C18:3, C18:2, C20:4, and C22:6 showed an excellent diagnostic ability to differentiate the patients with early stage BC from healthy controls, with the area under the receiver operating characteristics (ROC) curve of 0.953, a sensitivity of 83.3%, and a specificity of 87.1%. CONCLUSION Our findings suggest that these FFAs may be a valuable biomarker panel for the early-stage detection of BC.
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Affiliation(s)
- Yaping Zhang
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, PR China
| | - Lina Song
- Laboratory Medicine Center, China-Japan Union Hospital of Jilin University, Changchun 130033, PR China
| | - Ning Liu
- Central Laboratory, Jilin University Second Hospital, Changchun 130041, PR China
| | - Chengyan He
- Laboratory Medicine Center, China-Japan Union Hospital of Jilin University, Changchun 130033, PR China.
| | - Zhili Li
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, PR China.
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